REALLY FUN FACT for big cats cheetahs are fucking docile as shit
my grandfather ran a cheetah sanctuary in south africa and he’d just lie with them and sleep among them and they’d rub against him and chirp at him they’re big fucking babies
Another Fun Fact: Cheetahs are incredibly nervous animals. One of the (many) reason’s they’re going extinct is that cheetahs are so sensitive and nervous, some of them are literally too nervous to breed. Others will breed, but stress themselves out so much, they’ll lose their cubs.
So zoos with breeding programs had to figure out how to make cheetahs comfortable enough to first of all, get laid and secondly - not spazz themselves into miscarrying.
So what’d they do?
They gave the cheetah’s their very own Service Dogs!
The dogs make them feel safe, protected and secure!
Also! Cheetahs are not in fact classified as big cats, they are simply very large lesser cats, due to the fact that they purr, meow, chirp, and cannot roar. Also many cheetahs have learned to recognize wildlife photographers are friends and not foes, so they will just come up to people and be friendly occasionally as pictured at the top of the chain. Some will even leave their Cubs with photographers to look after while they hunt. So. Yeah. Cheetahs are great
this works because cheetahs are actually fairly social animals, and they look to members of their group for context on how worried they should be about any given Situation. but since cheetahs are also nervous social animals, they can work each other into an anxiety spiral pretty easily over things like “being in an enclosed habitat” and “there’s a guy over there”.
so by introducing a dog as a member of the group, the cheetahs will now look to the dog for context clues on how worried they should be! and the dog Is Not Worried At All, Thanks, so the cheetahs think everything must be chill even if they were personally unsure about it, and they stop being so freaked out about literally everything.
So the thing about cheetahs is it’s the males that are social. The females actually aren’t once the cubs are weaned, and having females have too much contact with each other will make it hard for them to get pregnant. They need their own, non-overlapping territories, with minimised female-female fenceline contact. Too much female-female contact stresses them out in general and makes it hard for them to conceive. The whole ‘I need to be chased to get in the mood’ thing is another thing that makes breeding hard for cheetahs, you need enough space so that that part of the breeding/courtship process can happen too.
Males on the other hand, form coalitions and are very social in their social group . Coalitions are usually 2-3 brothers that share food and resources and play together and it is adorable.
Cheetahs also usually have twins or more, and a cheetah that births a singleton will often abandon it. We don’t know why this happens but it does. But if you have another cheetah with cubs, you can sneak that cub in and she goes ‘oh another one, okay’ and the cub can be reared that way (the process of sneaking the cub in involves some scent transfer too iirc).
Monarto Safari Park in South Australia, which has one of the highest rates of cheetah breeding success, makes this work by giving the females their own territories but the males have their own shared space for that particular coalition. I very recommend going to check them out if you’re ever in the area, as it’s an amazing place doing a lot of great work in animal conservation and science and improving our understanding of what is needed to keep these animals happy and healthy. Also last time I was there I saw two rhinos playing tug of war with a stick and it was ADORABLE AS HECK.
For those of you with android devices, you can use the Android Debug Bridge (ADB) standalone app control program to get rid of all the bloatware, data mining, and AI crap - no coding needed!
There are also Android-based alternatives like GrapheneOS and LineageOS, which are pretty easy to install. These are unfortunately available for a more limited range of devices (Graphene is ironically Pixel only, while Lineage supports more), but it's very worth checking out whether one of them might work for your phone.
GrapheneOS is a security and privacy focused mobile OS with Android app compatibility.
LineageOS Android Distribution
Typing this from Graphene now, in fact. But, both of those take the Android Open Source Project, without all the bloatware--and largely de-Google the whole thing. They give you much more control over privacy and what the apps you choose to install can do and access on your phone.
I know Graphene sandboxes everything, including the optionally installed Google Play Services which a lot of apps unfortunately require to run. (Lineage uses an alternative to Play Services instead.) So, you can install what would normally be unacceptably intrusive apps and just lock them away from pulling any funny shit with your data, or phoning home. Including the couple of Google things I do still keep around.
I also prefer running much more transparent, privacy-respecting open source apps where possible. Besides the transparency, I'd rather avoid the shitty tech corps entirely where I can. There are pretty good alternatives available for a lot of the usual suspects.
AlternativeTo lets you find apps and software for Windows, Mac, Linux, iPhone, iPad, Android, Android Tablets, Web Apps, Online, Windows Tab
An alternative app store:
F-Droid is an installable catalogue of FOSS (Free and Open Source Software) applications for the Android platform. The client makes it easy
Text of tweet under the cut because it is loooong.
But... Stochastic Parrots.
Timnit Gebru was fired from Google in December 2020 for refusing to retract a research paper, and every single warning that paper made about large language models has now happened at a scale the industry spent 4 years trying to make people forget about.
Her name is Timnit Gebru.
She co-led the Ethical AI team at Google. She co-wrote a paper called "On the Dangers of Stochastic Parrots" with Emily Bender at the University of Washington and two other researchers. The paper was 14 pages long. It was submitted to a top AI ethics conference. And it was the reason Google decided that one of the most senior Black women in AI research could no longer work there.
The story Google told publicly was that she resigned. The story she told, confirmed by 2,695 of her colleagues in an open letter, was that she was fired by email while on vacation because she refused to either retract the paper or remove her name from it.
The paper had not even been published yet.
Here is what she actually wrote, and why every prediction inside it has now come true.
The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language. They called these systems stochastic parrots because they would repeat patterns from training data with statistical confidence and zero comprehension. The paper predicted that this apparent intelligence would fool both users and developers into trusting outputs that were structurally incapable of being reliable.
This was 2020. GPT-3 had just come out. The paper predicted the hallucination problem before anyone had a word for it.
The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it, because the optimization process rewards confident outputs, and confidence in language patterns tracks frequency in the training set.
The prediction was that hiring tools built on these models would discriminate against women. That healthcare triage tools would underperform on Black patients. That loan approval systems would entrench inequality while presenting their decisions as neutral algorithmic judgment.
Every one of those things has now been documented in deployment.
Amazon's hiring algorithm penalized resumes that contained the word "women" in any context. Healthcare risk scoring algorithms used by major US hospitals were found to systematically underestimate the medical needs of Black patients. Apple Card's credit algorithm gave wives credit lines 10x lower than their husbands for the same financial profile.
The third warning was about environmental cost. The paper calculated that training a single large language model produced emissions equivalent to the lifetime output of 5 cars. The prediction was that the race to scale would create an environmental footprint that would eventually rival entire industries.
In 2024, Google's emissions were up 48% from 2019, and the company explicitly blamed AI infrastructure. Microsoft's were up 29%, same reason. Both companies have now quietly abandoned the climate commitments they were publicly celebrating the year Gebru was fired.
The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit. Nobody at Google, OpenAI, Meta, or any other lab could tell you with confidence what was in the data their models were trained on. This was not a temporary problem to be solved later. It was a permanent feature of the approach.
In 2023, researchers discovered that the LAION-5B dataset, used to train Stable Diffusion and other major image models, contained thousands of images of child sexual abuse material. The companies that had trained on the dataset had no way of knowing. The paper predicted that category of failure 3 years before it was found.
The fifth warning was the one Google cared about most.
Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them. The internet would become a place where the dominant voice was a statistical average of dominant voices, presented as a neutral assistant. Languages underrepresented in the training data would degrade over time as more web content was generated by these systems and fed back into the next training run.
This is now happening in real time. A 2024 study found that 57% of new web content in English is AI-generated or AI-assisted. Researchers studying low-resource languages have documented active degradation in translation quality, because the synthetic content fed back into training is itself worse in those languages.
The paper Google fired her for predicted the model collapse problem before model collapse had a name.
The mechanism behind why this all happened is the part of her work that nobody quotes.
Gebru's argument was not that AI is dangerous in some abstract sci-fi sense. Her argument was that AI is dangerous in a very specific structural sense. The technology was being built by a small group of researchers who shared similar backgrounds, worked at similar companies, and were rewarded for shipping products faster than competitors. The incentive structure made it impossible for safety, ethics, and bias concerns to slow anything down. Anyone inside the system who raised those concerns was either ignored, sidelined, or removed.
She was making that argument from inside Google.
Then Google proved her right by removing her.
The team Google had built to make sure their AI was safe was dismantled in 90 days because they did the job they had been hired to do. Margaret Mitchell, the other co-lead of the Ethical AI team, was fired two months after Gebru for searching through her own emails for evidence of how Gebru had been treated.
Gebru did not stop. She founded DAIR, the Distributed AI Research Institute, in 2021. The mission is to do AI research outside the control of the companies that have a financial interest in not hearing the answers.
Every prediction in the Stochastic Parrots paper has now been validated by deployment. Hallucinations are an industry-wide problem the largest labs cannot solve. Bias amplification has been documented in hiring, healthcare, lending, and criminal justice. Environmental costs are larger than entire small countries. Training data audits remain impossible. Model collapse is an active research crisis at every major lab.
The question worth sitting with is the one almost no one in the industry will say out loud.
Every researcher with the technical credibility to call out these problems watched what happened to her in December 2020 and made a calculation about their own career. The number of people willing to speak publicly about safety and ethics issues inside the major AI labs collapsed after that firing and has not recovered.
The researcher Google fired for warning about exactly what is now happening was right.
The company that fired her is now the second-largest deployer of the technology she warned about.
And the people inside that company who agree with her are not allowed to say so.
And yet people act surprised when their CEO was assassinated when the real surprise is that it's not happening on a regular basis across the entire industry.
The crazy thing is, ninety-nine times out of a hundred, if you asked me on any given day "Would like to see a picture of some genitals?" my answer would be "😰 No, that's... No, thank you. I'm okay, actually." I have nothing but the utmost respect for people who do engage with the penis side of the internet, but personally, I've spent the better part of two decades doing all I can NOT to have pictures of dick and balls or sexy bikini babe buttcheeks blasted onto my retinas constantly. And yet... to be denied the penis? To have a jumped up pile of javascript tell me, a grown adult with an air fryer and an outstanding council tax bill, that I cannot be trusted to withstand the sight of a bare nipple unless I let it scan my drivers' license? I will move heaven and earth to see that fucking nipple, friend. I will walk a thousand miles barefoot on hot coals before I give you big brother bitches my passport number. A thousand miles through the desert with five VPNs just to press my face up against the glass and see the last uncensored picture of two My Little Pony Characters sixty-nining each other, and I don't even want! to look at it! But I will! I must! for the sake of our fucking democracy!
absolutely hate it when the pleasurable activity procrastination hits. i’m going to do something fun that brings me joy but not yet. yeah, not yet. not yet. maybe i shouldn’t do it at all, it’s not that fun
izzy806
tangentwithtanner
prguitarman
ellievsbear
snowghoul
